Finding Anomalies in China

119 Pages Posted: 12 Jan 2023

See all articles by Kewei Hou

Kewei Hou

Ohio State University (OSU) - Department of Finance

Fang Qiao

University of International Business and Economics (UIBE) - School of Banking and Finance

Xiaoyan Zhang

Tsinghua University - PBC School of Finance

Date Written: January 11, 2023

Abstract

To study the cross-section of returns in the Chinese stock market, we follow the anomaly literature and construct 454 strategies between 2000 and 2020, based on 208 firm-level trading and accounting signals. With the conventional single-testing t-statistic cutoff of 1.96, 101 strategies have significant value-weighted raw returns, and 20 remain significant after risk adjustments. To avoid false discoveries, we recalibrate the t-statistic cutoff to 2.85 to accommodate multiple testing. 36 strategies survive the higher hurdle rate in value-weighted raw returns, while none remains significant after risk adjustments. When we use machine learning techniques to combine information from multiple signals, the resulting composite strategies mostly have significant returns after risk adjustments, even with the higher t-statistic cutoff. We relate Chinese anomaly returns to aggregate economic conditions and find that they comove with financial market development, accounting quality, market liquidity, and government regulations.

Keywords: China, anomalies, liquidity, multiple tests, composite strategies

JEL Classification: G12, G1

Suggested Citation

Hou, Kewei and Qiao, Fang and Zhang, Xiaoyan, Finding Anomalies in China (January 11, 2023). Fisher College of Business Working Paper No. 2023-03-002, Charles A. Dice Center Working Paper No. 2023-002, PBCSF-NIFR Research Paper Forthcoming, Available at SSRN: https://ssrn.com/abstract=4322815 or http://dx.doi.org/10.2139/ssrn.4322815

Kewei Hou (Contact Author)

Ohio State University (OSU) - Department of Finance ( email )

2100 Neil Avenue
Columbus, OH 43210-1144
United States
614-292-0552 (Phone)
614-292-2418 (Fax)

Fang Qiao

University of International Business and Economics (UIBE) - School of Banking and Finance ( email )

No.10, Huixindong Street
Chaoyang District
Beijing, 100029
China

Xiaoyan Zhang

Tsinghua University - PBC School of Finance ( email )

No. 43, Chengdu Road
Haidian District
Beijing 100083
China

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